Juliane Mueller
Cited by
Cited by
SO-MI: A surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problems
J Müller, CA Shoemaker, R Piché
Computers & Operations Research 40 (5), 1383-1400, 2013
Influence of Ensemble Surrogate Models and Sampling Strategy on the Solution Quality of Algorithms for Computationally Expensive Black-Box Global Optimization Problems
J Müller, CA Shoemaker
Journal of Global Optimization 60 (2), 123-144, 2014
Mixture surrogate models based on Dempster-Shafer theory for global optimization problems
J Müller, R Piché
Journal of Global Optimization 51, 79-104, 2011
MISO: mixed-integer surrogate optimization framework
J Müller
Optimization and Engineering, 2015
Classical optimizers for noisy intermediate-scale quantum devices
W Lavrijsen, A Tudor, J Müller, C Iancu, W De Jong
2020 IEEE international conference on quantum computing and engineering (QCE …, 2020
SO-I: A Surrogate Model Algorithm for Expensive Nonlinear Integer Programming Problems Including Global Optimization Applications
J Müller, CA Shoemaker, R Piche
Journal of Global Optimization 59 (4), 865-889, 2014
Approximative solutions to the bicriterion vehicle routing problem with time windows
J Müller
European Journal of Operational Research 202 (1), 223-231, 2010
SOCEMO: surrogate optimization of computationally expensive multiobjective problems
J Müller
INFORMS Journal on Computing 29 (4), 581-596, 2017
MATSuMoTo: The MATLAB surrogate model toolbox for computationally expensive black-box global optimization problems
J Mueller
arXiv preprint arXiv:1404.4261, 2014
Surrogate optimization of deep neural networks for groundwater predictions
J Müller, J Park, R Sahu, C Varadharajan, B Arora, B Faybishenko, ...
Journal of Global Optimization 81, 203-231, 2021
GOSAC: global optimization with surrogate approximation of constraints
J Müller, JD Woodbury
Journal of Global Optimization 69 (1), 117-136, 2017
CH4 Parameter Estimation in CLM4.5bgc Using Surrogate Global Optimization
J Muller, R Paudel, CA Shoemaker, J Woodbury, Y Wang, N Mahowald
Geoscientific Model Development 8 (10), 3285-3310, 2015
User guide for modularized surrogate model toolbox
J Müller
Tampere University of Technology, 2012
Surrogate optimization of computationally expensive black-box problems with hidden constraints
J Müller, M Day
INFORMS Journal on Computing 31 (4), 689-702, 2019
Impact of input feature selection on groundwater level prediction from a multi-layer perceptron neural network
RK Sahu, J Müller, J Park, C Varadharajan, B Arora, B Faybishenko, ...
Frontiers in Water 2, 573034, 2020
Surrogate model algorithms for computationally expensive black-box global optimization problems
J Müller
Tampere University of Technology, 2012
An efficient algorithm for automatic structure optimization in x-ray standing-wave experiments
O Karslıoğlu, M Gehlmann, J Müller, S Nemšák, JA Sethian, A Kaduwela, ...
Journal of Electron Spectroscopy and Related Phenomena 230, 10-20, 2019
Adaptive Gaussian process surrogates for Bayesian inference
T Takhtaganov, J Müller
arXiv preprint arXiv:1809.10784, 2018
Characterization of free-standing InAs quantum membranes by standing wave hard x-ray photoemission spectroscopy
G Conti, S Nemšák, CT Kuo, M Gehlmann, C Conlon, A Keqi, ...
APL materials 6 (5), 058101, 2018
Cosmic inference: Constraining parameters with observations and a highly limited number of simulations
T Takhtaganov, Z Lukić, J Müller, D Morozov
The Astrophysical Journal 906 (2), 74, 2021
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Articles 1–20